{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "0_ctr_data_explore.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/henrygas/ctr/blob/master/0_ctr_data_explore.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_kRopNKYLLVW",
        "colab_type": "text"
      },
      "source": [
        "## 0. 准备工作"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rACuQUQLL7K-",
        "colab_type": "text"
      },
      "source": [
        "### 0.1 在本地计算机上，先读取前10000条数据，并保存这批数据到csv中"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qlbm7zd08GOz",
        "colab_type": "code",
        "outputId": "8362b9a0-6ba2-47f4-f815-c73aee9cc9c6",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "data_path = \"./data/train.csv\"\n",
        "chunks = pd.read_csv(data_path, iterator=True)\n",
        "chunk = chunks.get_chunk(10000)\n",
        "print(type(chunk))\n",
        "print(chunk.info())\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 10000 entries, 0 to 9999\n",
            "Data columns (total 24 columns):\n",
            "id                  10000 non-null uint64\n",
            "click               10000 non-null int64\n",
            "hour                10000 non-null int64\n",
            "C1                  10000 non-null int64\n",
            "banner_pos          10000 non-null int64\n",
            "site_id             10000 non-null object\n",
            "site_domain         10000 non-null object\n",
            "site_category       10000 non-null object\n",
            "app_id              10000 non-null object\n",
            "app_domain          10000 non-null object\n",
            "app_category        10000 non-null object\n",
            "device_id           10000 non-null object\n",
            "device_ip           10000 non-null object\n",
            "device_model        10000 non-null object\n",
            "device_type         10000 non-null int64\n",
            "device_conn_type    10000 non-null int64\n",
            "C14                 10000 non-null int64\n",
            "C15                 10000 non-null int64\n",
            "C16                 10000 non-null int64\n",
            "C17                 10000 non-null int64\n",
            "C18                 10000 non-null int64\n",
            "C19                 10000 non-null int64\n",
            "C20                 10000 non-null int64\n",
            "C21                 10000 non-null int64\n",
            "dtypes: int64(14), object(9), uint64(1)\n",
            "memory usage: 1.8+ MB\n",
            "None\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mtCL9XqNKxqD",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "data_part_path = \"./data/train_part.csv\"\n",
        "chunk.to_csv(data_part_path, index=False, header=True)\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wf-8JWJ6MDsg",
        "colab_type": "text"
      },
      "source": [
        "### 0.2 挂载Google云盘"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hrWxFkClMHBE",
        "colab_type": "code",
        "outputId": "359d9aca-a327-44ed-ffed-e46fc1ec93b8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount(\"/content/drive\")"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ECQzsW9nMoOq",
        "colab_type": "text"
      },
      "source": [
        "### 0.3 定位当前工作目录"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HR-b53PNMqHb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import os\n",
        "os.chdir(\"./drive/My Drive/app/ctr\")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SWIFjlxjMvt1",
        "colab_type": "code",
        "outputId": "aac795d5-21d8-4db8-9057-4b68dd9d4c9e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "!ls"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "data  model  out\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z7RTYy5FLgHu",
        "colab_type": "text"
      },
      "source": [
        "## 1. 数据探索"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Aq9a3bwPLkVl",
        "colab_type": "text"
      },
      "source": [
        "### 1.1 读取train_part.csv数据，并查看基本信息"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_OTolv4wKxqH",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JCF4PtdDNTwZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "data_part_path = \"./data/train_part.csv\"\n",
        "train_data = pd.read_csv(data_part_path)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fxrIbKXDNa9V",
        "colab_type": "code",
        "outputId": "910203b5-9fbd-412b-fdbe-b0170231d40b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 224
        }
      },
      "source": [
        "train_data.head()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>click</th>\n",
              "      <th>hour</th>\n",
              "      <th>C1</th>\n",
              "      <th>banner_pos</th>\n",
              "      <th>site_id</th>\n",
              "      <th>site_domain</th>\n",
              "      <th>site_category</th>\n",
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              "      <th>app_domain</th>\n",
              "      <th>app_category</th>\n",
              "      <th>device_id</th>\n",
              "      <th>device_ip</th>\n",
              "      <th>device_model</th>\n",
              "      <th>device_type</th>\n",
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              "      <th>C14</th>\n",
              "      <th>C15</th>\n",
              "      <th>C16</th>\n",
              "      <th>C17</th>\n",
              "      <th>C18</th>\n",
              "      <th>C19</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1000009418151094273</td>\n",
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              "      <td>0</td>\n",
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              "      <td>1722</td>\n",
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              "      <td>-1</td>\n",
              "      <td>79</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10000169349117863715</td>\n",
              "      <td>0</td>\n",
              "      <td>14102100</td>\n",
              "      <td>1005</td>\n",
              "      <td>0</td>\n",
              "      <td>1fbe01fe</td>\n",
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              "      <td>50</td>\n",
              "      <td>1722</td>\n",
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              "      <td>35</td>\n",
              "      <td>100084</td>\n",
              "      <td>79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>10000371904215119486</td>\n",
              "      <td>0</td>\n",
              "      <td>14102100</td>\n",
              "      <td>1005</td>\n",
              "      <td>0</td>\n",
              "      <td>1fbe01fe</td>\n",
              "      <td>f3845767</td>\n",
              "      <td>28905ebd</td>\n",
              "      <td>ecad2386</td>\n",
              "      <td>7801e8d9</td>\n",
              "      <td>07d7df22</td>\n",
              "      <td>a99f214a</td>\n",
              "      <td>b3cf8def</td>\n",
              "      <td>8a4875bd</td>\n",
              "      <td>1</td>\n",
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              "      <td>320</td>\n",
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              "      <td>35</td>\n",
              "      <td>100084</td>\n",
              "      <td>79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>10000640724480838376</td>\n",
              "      <td>0</td>\n",
              "      <td>14102100</td>\n",
              "      <td>1005</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>1722</td>\n",
              "      <td>0</td>\n",
              "      <td>35</td>\n",
              "      <td>100084</td>\n",
              "      <td>79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>10000679056417042096</td>\n",
              "      <td>0</td>\n",
              "      <td>14102100</td>\n",
              "      <td>1005</td>\n",
              "      <td>1</td>\n",
              "      <td>fe8cc448</td>\n",
              "      <td>9166c161</td>\n",
              "      <td>0569f928</td>\n",
              "      <td>ecad2386</td>\n",
              "      <td>7801e8d9</td>\n",
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              "      <td>2161</td>\n",
              "      <td>0</td>\n",
              "      <td>35</td>\n",
              "      <td>-1</td>\n",
              "      <td>157</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     id  click      hour    C1  ...  C18 C19     C20  C21\n",
              "0   1000009418151094273      0  14102100  1005  ...    0  35      -1   79\n",
              "1  10000169349117863715      0  14102100  1005  ...    0  35  100084   79\n",
              "2  10000371904215119486      0  14102100  1005  ...    0  35  100084   79\n",
              "3  10000640724480838376      0  14102100  1005  ...    0  35  100084   79\n",
              "4  10000679056417042096      0  14102100  1005  ...    0  35      -1  157\n",
              "\n",
              "[5 rows x 24 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RUsxx-1uNgPR",
        "colab_type": "code",
        "outputId": "2f9fba56-420e-4e35-81d7-d2a8e8898bb5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 539
        }
      },
      "source": [
        "train_data.info()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 10000 entries, 0 to 9999\n",
            "Data columns (total 24 columns):\n",
            "id                  10000 non-null uint64\n",
            "click               10000 non-null int64\n",
            "hour                10000 non-null int64\n",
            "C1                  10000 non-null int64\n",
            "banner_pos          10000 non-null int64\n",
            "site_id             10000 non-null object\n",
            "site_domain         10000 non-null object\n",
            "site_category       10000 non-null object\n",
            "app_id              10000 non-null object\n",
            "app_domain          10000 non-null object\n",
            "app_category        10000 non-null object\n",
            "device_id           10000 non-null object\n",
            "device_ip           10000 non-null object\n",
            "device_model        10000 non-null object\n",
            "device_type         10000 non-null int64\n",
            "device_conn_type    10000 non-null int64\n",
            "C14                 10000 non-null int64\n",
            "C15                 10000 non-null int64\n",
            "C16                 10000 non-null int64\n",
            "C17                 10000 non-null int64\n",
            "C18                 10000 non-null int64\n",
            "C19                 10000 non-null int64\n",
            "C20                 10000 non-null int64\n",
            "C21                 10000 non-null int64\n",
            "dtypes: int64(14), object(9), uint64(1)\n",
            "memory usage: 1.8+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YKv5InRMNiaD",
        "colab_type": "text"
      },
      "source": [
        "共计有24列，其中click列为标签，其他列均为特征；在特征列中，int64类型有14列，object类型有9列，uint64类型有1列(id，属于无意义的列)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q1d09I4VN9lf",
        "colab_type": "code",
        "outputId": "c6ed8f06-acd8-4ef1-d344-9ffd920bc99b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        }
      },
      "source": [
        "train_data.describe()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "    .dataframe tbody tr th {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>click</th>\n",
              "      <th>hour</th>\n",
              "      <th>C1</th>\n",
              "      <th>banner_pos</th>\n",
              "      <th>device_type</th>\n",
              "      <th>device_conn_type</th>\n",
              "      <th>C14</th>\n",
              "      <th>C15</th>\n",
              "      <th>C16</th>\n",
              "      <th>C17</th>\n",
              "      <th>C18</th>\n",
              "      <th>C19</th>\n",
              "      <th>C20</th>\n",
              "      <th>C21</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1.000000e+04</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.0</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>10000.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>9.795641e+18</td>\n",
              "      <td>0.170600</td>\n",
              "      <td>14102100.0</td>\n",
              "      <td>1005.059900</td>\n",
              "      <td>0.195900</td>\n",
              "      <td>1.068200</td>\n",
              "      <td>0.204500</td>\n",
              "      <td>17711.693800</td>\n",
              "      <td>318.478000</td>\n",
              "      <td>56.986400</td>\n",
              "      <td>1967.605900</td>\n",
              "      <td>0.789500</td>\n",
              "      <td>125.622400</td>\n",
              "      <td>37746.299500</td>\n",
              "      <td>88.260300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2.853038e+18</td>\n",
              "      <td>0.376178</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.103193</td>\n",
              "      <td>0.404895</td>\n",
              "      <td>0.601984</td>\n",
              "      <td>0.646469</td>\n",
              "      <td>3139.296362</td>\n",
              "      <td>11.492429</td>\n",
              "      <td>37.425508</td>\n",
              "      <td>385.160315</td>\n",
              "      <td>1.228878</td>\n",
              "      <td>234.039047</td>\n",
              "      <td>48516.401341</td>\n",
              "      <td>45.153569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.004777e+16</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>14102100.0</td>\n",
              "      <td>1001.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>375.000000</td>\n",
              "      <td>216.000000</td>\n",
              "      <td>36.000000</td>\n",
              "      <td>112.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>35.000000</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>13.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1.024754e+19</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>14102100.0</td>\n",
              "      <td>1005.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>15704.000000</td>\n",
              "      <td>320.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>1722.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>35.000000</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>61.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1.063018e+19</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>14102100.0</td>\n",
              "      <td>1005.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>17654.000000</td>\n",
              "      <td>320.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>1993.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>35.000000</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>79.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1.100749e+19</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>14102100.0</td>\n",
              "      <td>1005.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>20362.000000</td>\n",
              "      <td>320.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>2307.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>39.000000</td>\n",
              "      <td>100083.000000</td>\n",
              "      <td>117.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.138513e+19</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>14102100.0</td>\n",
              "      <td>1010.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>21705.000000</td>\n",
              "      <td>728.000000</td>\n",
              "      <td>480.000000</td>\n",
              "      <td>2497.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>1835.000000</td>\n",
              "      <td>100248.000000</td>\n",
              "      <td>157.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id         click  ...            C20           C21\n",
              "count  1.000000e+04  10000.000000  ...   10000.000000  10000.000000\n",
              "mean   9.795641e+18      0.170600  ...   37746.299500     88.260300\n",
              "std    2.853038e+18      0.376178  ...   48516.401341     45.153569\n",
              "min    1.004777e+16      0.000000  ...      -1.000000     13.000000\n",
              "25%    1.024754e+19      0.000000  ...      -1.000000     61.000000\n",
              "50%    1.063018e+19      0.000000  ...      -1.000000     79.000000\n",
              "75%    1.100749e+19      0.000000  ...  100083.000000    117.000000\n",
              "max    1.138513e+19      1.000000  ...  100248.000000    157.000000\n",
              "\n",
              "[8 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9pTItqTUOCVG",
        "colab_type": "text"
      },
      "source": [
        "从统计信息里可以看出：\n",
        "+ click,banner_pos,device_conn_type的分位数均为0，说明是稀疏的，只有少量非零值；\n",
        "+ hour均为同一取值，可能原始数据是按照时序排列的，所以只取头部数据，可能会忽略hour这个特征；\n",
        "+ C14~C21列的方差都比较大, 说明取值离散性比较大；\n",
        "+ device_type的分位数均为1.000000,说明大部分样本的device_type取值都集中在取值1上，其他的取值较少。"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CCvFfjciPxdb",
        "colab_type": "text"
      },
      "source": [
        "### 1.2 观察类别型特征的统计数据"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3znRYZawP74U",
        "colab_type": "code",
        "outputId": "60c27ebf-f877-4ad6-fdd8-61d97de5606b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 71
        }
      },
      "source": [
        "train_data.click.value_counts()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    8294\n",
              "1    1706\n",
              "Name: click, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TGEscqzSQTj9",
        "colab_type": "text"
      },
      "source": [
        "10000个样本里，只有1706个click=1，剩余的都是未被点击过的"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FnjoJ9kHQeCo",
        "colab_type": "code",
        "outputId": "259dacc6-914e-4d8d-cd22-f0eaaeed9498",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "c_name_list = [\"C1\"]\n",
        "for i in range(14, 22):\n",
        "  c_name_list.append(\"C{}\".format(i))\n",
        "c_name_list"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['C1', 'C14', 'C15', 'C16', 'C17', 'C18', 'C19', 'C20', 'C21']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S_k8tjG3Q8Lg",
        "colab_type": "code",
        "outputId": "784ded3c-035b-43ed-90ef-f9be6dadb417",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "# plt.figure(figsize=(8, 120))\n",
        "for c_name in c_name_list:\n",
        "  train_data.hist(column=c_name, bins=20, grid=False)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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q4GZgcZIjqurbVbWxHe/7DH6pl4y/9aM3ivEASPJbwOHAl8bf6vEYxVi0X+JFVbWuHfOJ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\n5zoEvtQAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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BtcBhwI1V9egITjXkEtIUNZ3mO53mCtNrvtNprjBB55uqGu8xSJLG2URZJpIkjSPDQJI0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\n720AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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S1GVYSJK6piYskpyT5L4kc0kuXezxSJIeNxVhkeQI4G+A1wKnAr+R5NTFHZUkab+pCAvg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\nSV2GhSSp6/8Bkfvn+JBeHZYAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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kdcTQl6SOGPqS1JE5Qz/JziRHkjw4VDsryd4kj7br1a2eJB9IMpVkf5ILhtbZ2to/mmTr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\n89MAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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3A99O8kCr/QFwA3BrkquAx4DL2rI7gEuAaeB54EqAqjqQ5Drgvtbu2qo6MJZRSJJGMm/o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\nYuhLUkf+P/ySJ6k0Q26tAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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uvqmq7wLvmGZblwOXz76bkqRh8BO5ktQhhr4kdYihL0kdYuhLUocY+pLUIYa+JHWIoS9J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\nDjH0JalDDH1J6hBDX5I65P8Ddkcmb4PiJsgAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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F8OhQuz2tNlVdkjRPDvsmcFUVULPQFwCSbE6yK8mu/fv3z9ZmJUkHOdQAeKJd2qG972v1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\ndcoAkKROGQCS1Kn/D1yjfZdsrrmcAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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1jMEvSR1j8EtSxxj8ktQxBr8kdYzBL0kdM23wJ9mSZH+Se/pqJyTZnuSB9nNJqyfJR5KM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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BZMwxryORFuv",
        "colab_type": "text"
      },
      "source": [
        "可以看到，以C开头的几个类别型特征，其取值都较为不均衡，集中在少量的几个取值上。"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KKDSXV2aRUe1",
        "colab_type": "text"
      },
      "source": [
        "### 1.3 研究每个单个特征与标签的关系"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WOC_KwGRRfGP",
        "colab_type": "code",
        "outputId": "98ac9780-b919-4ad3-9ba7-b87e4459b96e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        }
      },
      "source": [
        "train_data.isnull().sum()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                  0\n",
              "click               0\n",
              "hour                0\n",
              "C1                  0\n",
              "banner_pos          0\n",
              "site_id             0\n",
              "site_domain         0\n",
              "site_category       0\n",
              "app_id              0\n",
              "app_domain          0\n",
              "app_category        0\n",
              "device_id           0\n",
              "device_ip           0\n",
              "device_model        0\n",
              "device_type         0\n",
              "device_conn_type    0\n",
              "C14                 0\n",
              "C15                 0\n",
              "C16                 0\n",
              "C17                 0\n",
              "C18                 0\n",
              "C19                 0\n",
              "C20                 0\n",
              "C21                 0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jXMt4pm5hFcX",
        "colab_type": "text"
      },
      "source": [
        "可见没有缺失值"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mrLwNazHhH5g",
        "colab_type": "code",
        "outputId": "7cf817f8-4d27-4be3-a325-30ed811e3a14",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "for column in c_name_list:\n",
        "  sns.catplot(x=column, y=\"click\", data=train_data)\n",
        "  plt.xticks(rotation=90, fontsize=10)\n",
        "  plt.show()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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WpEYMsCQ1YoAlqREDLEmNGGBJasQAS1IjBliSGjHAktSIAZakRgywJDVigCWpEQMsSY0Y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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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cWBx/LwF2dNEfIYToOt0U1TXA1mx7W9yX817gTWa2Dfgc8K5Ohszs7Wa23szW7927txu+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\nSUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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6d+Fny4esmAJs3vHvn7IbvPtmmPOKJqbrOkcvPvol7+Pud9zdgUkmlrX33U/Pnnuyy5z9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\n/wOZFGUIn1puSAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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2Z+PG5No7Huanjz/DIf3TePLZtew/aypz95zGpAiWLV9FBMyeNoVn1qxj8KnnOO2Y/Zgz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\nvC+puSXupIAAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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hUkTgAD3pVjxQJzCBttjVU6Q62g9HcW1xnQLcjqde8q+VBLrwb4uh7SawpcIc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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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26ENwy7fhju/BIyvhqSdhx8lw2Emw8nq49WLYZQZM2gPuXwo7PBemHga7HwjrH4NHV8N+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\nwQ4AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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YTfcfh3N2HVO0zE/u3j3/QdWVDCnzur/skFFdwx/bs/iP2sBKeO+OfbvMUllp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\nTkSuQmCC\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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lT8yPp7tc5JSJMzFyrOzYQ95aKZTLcR9S+7nDllR+fz5J5bXFjSTeOXPyTJbv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\nyACJqRBCZIDEVAghMkBiKoQQGfD/ASBkmCthwce7AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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vpQb77BTtw016cPqY1OtNG5oZcqP6l3HG+NzAPHdiGaP6ZT7vJw4r5eP7l1MR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\nAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "whXiJFMnhqKG",
        "colab_type": "text"
      },
      "source": [
        "通过观察，\n",
        "+ 对click取值影响较大的特征有C1\n",
        "+ 个别取值下，对click取值影响较大的特征，有C15,C16,C18\n",
        "+ 总体来看，对click取值影响一般的特征，有C14,C17,C19,C20,C21"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FHSJJmv-inJ-",
        "colab_type": "text"
      },
      "source": [
        "接下来分析剩余的特征\n",
        "+ 认为id与click没有必然关系; <br/>\n",
        "+ hour因为目前取的样本里只有一个取值，所以暂时不研究它;<br/>\n",
        "+ 接下来分别研究banner_pos, site_id, site_domain, site_category, app_id, app_domain, app_category, device_id, device_ip, device_model, device_type, device_conn_type与标签列click取值的关系"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wZKlibS8hzU7",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "e0a48ee4-e334-45ed-dac0-474e23f96a8c"
      },
      "source": [
        "sns.catplot(x=\"banner_pos\", y=\"click\", data=train_data)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f1119054e48>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWAAAAFgCAYAAACFYaNMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/wAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4XOuRPkWiKB4",
        "colab_type": "text"
      },
      "source": [
        "可见，bannder_pos为0,1的时候，标签为1和0的概率相当;<br/>\n",
        "但当banner_pos为4时，标签全部为0;<br/>\n",
        "当banner_pos为5时，标签全部为1;<br/>\n",
        "这说明banner_pos的取值，对标签的影响很大。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_SKkuwPfii3P",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "62fb9bf3-2140-48f8-a3cc-3dd38e3da0c5"
      },
      "source": [
        "sns.catplot(x=\"site_id\", y=\"click\", data=train_data)"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f111938a160>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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H3NRUx4HeZLoP2JfheERE5pVChn2vBHan5vcAVzfVeS/wNTP7FWAB8IYMxyMiMq+Evgl3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\nAlhEJBAFsIhIIApgEZFA/j+M0Wyiy6d5dQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jWyhrrDplSZV",
        "colab_type": "text"
      },
      "source": [
        "目测site_id对click的取值有一定影响，但要看site_id的取值, 在site_id取比较靠右的值时，看上去click取0的概率大一些。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oFjSlSNvlXKe",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "3aa2ed67-6f04-4ef9-b194-fac42db206d9"
      },
      "source": [
        "sns.catplot(x=\"site_domain\", y=\"click\", data=train_data)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f111938a9b0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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lM+XNm5s9s2q8r51NTNS2MY2yyfr1IstqZzCTrvM/0W6ULcseqzJlkUPkcaZi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\nAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "17FW68wcl7vA",
        "colab_type": "text"
      },
      "source": [
        "site_domain对click取值的影响，跟site_id对click取值的影响一致，根据这个现象推测，site_id可能跟site_domain表达同样的信息，后续再看看site_id跟site_domain相关性，如果高度相关的话，则可判定site_id和site_domain属于重复特征，则在数据预处理的时候，可以去掉其中一个特征。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "x-8V5cetmevF",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "495e050b-20de-46a7-a456-02f1ca57d344"
      },
      "source": [
        "sns.catplot(x=\"site_category\", y=\"click\", data=train_data)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f1115596b00>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fzK6J998P+BLQYmaPkkL2WlIY9zezW4B3RvmLgZnuvtjMPgF8hbRvj4/5uwAL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\nSCEsIpKRQlhEJKP/A1EoAMEg8HNRAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-LKpGfjnmpWA",
        "colab_type": "text"
      },
      "source": [
        "通过图中可以看出，site_category对click的取值影响还是比较大的，在靠右的大部分取值下，click取0的概率大于取1的概率，在中间的个别取值下，倒是对click的取值没啥影响。猜测可能是因为不同的网站类别，本身的用户点击习惯是区别较大的，这个特征可能属于一个强特征。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ILvDn-kCnHGH",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "7b4b01f6-2509-4cef-aaf6-7bc544279067"
      },
      "source": [
        "sns.catplot(x=\"app_id\", y=\"click\", data=train_data)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f11190ef828>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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BLCISiAJYRCQQBbCISCAKYBGRQFoawGZ2uZk9aGbbzOzaJu0nm9mtZna3mW00s1e1sh4R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\nAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VJ9DhnqAnQRM",
        "colab_type": "text"
      },
      "source": [
        "app_id, 又一个对click取值影响较大的特征，对于大部分app_id取值，click取0的概率大大高于取1的概率，预备作为一个比较强的特征对待吧。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "knvtyRAPnf66",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "392d58f3-360a-4e81-e682-e612dcaea71e"
      },
      "source": [
        "sns.catplot(x=\"app_domain\", y=\"click\", data=train_data)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f11155b39b0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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5Zja1RLkRwKXAi+Wqi4jIYFXOnvA0YIlzbplzrhO4AzijRLnvAz8EOspYFxGRQamcITwR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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4BKpS65anotx",
        "colab_type": "text"
      },
      "source": [
        "app_domain，对click的取值影响较大，属于强特征，这可能是对于某些域名的APP来说，其点击率本来就不高，即click取0的概率远大于取1的概率。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kCaea0P2pSNj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "91e3c0bb-940d-4985-9e7d-14b48682f292"
      },
      "source": [
        "sns.catplot(x=\"app_category\", y=\"click\", data=train_data)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f1114dbccc0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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UwiIiGSmERUQyUgiLiGSkEBYRyUghLCKSkUJYRCQjhbCISEYKYRGRjBTCIiIZKYRFRDJS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\nQmCC\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PNhlOOkhpyZI",
        "colab_type": "text"
      },
      "source": [
        "app_category对click的取值影响也很大，猜测是因为不同的APP类型，用户的点击率本身就有很大差别，所以可以将app_category看作强特征。"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "86PqOLQ4qUSI",
        "colab_type": "text"
      },
      "source": [
        "**以上跟site和app相关的特征，判断属于平台方的特征，接下来的特征，判断属于用户的个人特征**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E4BClMQeqCJg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "1fe01fef-dc0b-46e6-ca2d-4c5f78cea1ca"
      },
      "source": [
        "sns.catplot(x=\"device_id\", y=\"click\", data=train_data)"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f1114d6a0f0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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lkg/ZNjX1eQx4FYCZnUESwLrEFZE5IbcAdvcKcD1wG/AgyU873G9mHzazy9Nu7wauM7Of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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HWaHTfs0r-jn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 233
        },
        "outputId": "d1e7e59b-65e9-434a-a5d6-f24c7bcb1c11"
      },
      "source": [
        "train_data.device_id.value_counts()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "a99f214a    8724\n",
              "c357dbff      17\n",
              "a167aa83       9\n",
              "3c0208dc       9\n",
              "31da1bd0       8\n",
              "            ... \n",
              "be55fdba       1\n",
              "4c78cc4f       1\n",
              "11190a5f       1\n",
              "dacad7fd       1\n",
              "eff4290a       1\n",
              "Name: device_id, Length: 1075, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "emHpHSVTqoGU",
        "colab_type": "text"
      },
      "source": [
        "device_id对click的影响看上去一般，\n",
        "+ 但由于device_id取值数量较多，所以图中可能很难看出细节，可以暂时把device_id作为一般特征，后续还要看看device_id跟click的相关性，再作判断。\n",
        "+ device_id取值比较集中在a99f214a上，不太均衡，猜测a99f214a可能是device_id的默认值，当device_id不能取到真实值的时候，统一取这个值。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5JS946zhqujv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "8b1dab3c-c1aa-4bdd-83c5-3b25ebea5321"
      },
      "source": [
        "\n",
        "sns.catplot(x=\"device_ip\", y=\"click\", data=train_data)\n"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f110a315f98>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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WA3hvZj7RLjTzZ8xmSJK0O2w1gJ+MiBe3C82Poj01myFJ0u6wpR9DA34RuDUiHgQCuBB4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\nqRADWJIK+f9cHuJFa/QviwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JduXkIkb1FBl",
        "colab_type": "text"
      },
      "source": [
        "device_ip不同的取值，对click的取值几乎没有影响，click取1和0的概率基本是相当的。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kfUjsijLqS7k",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "33a93082-c02b-4d98-8fc1-2bde719e7fe7"
      },
      "source": [
        "sns.catplot(x=\"device_model\", y=\"click\", data=train_data)"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f10fe391f60>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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6tDhCxrkzGbPAgSPlV8Qx6Hh4fiqfn8XqzbHWAjKN1FcvhGL0yltDVoV7txor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\nmSXy/wELKtC8SFOMIQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e74Imhvt1r-v",
        "colab_type": "text"
      },
      "source": [
        "device_model不同的取值，对click的取值也几乎没有影响，click取1和0的概率基本是相当的。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qbrIGfnq1y34",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "e974a52d-1199-4bbb-af12-aef0f97902bb"
      },
      "source": [
        "sns.catplot(x=\"device_type\", y=\"click\", data=train_data)"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f10fb715b70>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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nAu8Dzulqpv3xtqtu5a++8u2+rPXFi1/Ok45e1Je1BtK7jurzet/p73oD5rQrTmMHO/qy\n1td+6mt9WWdQTTzyCN9+9yV89xOf2O81cuihLL/sIyxetaqPkx2YLs+ATwc2VNXGqtoOXAWctdsx\nZwFX9P7+F8ArkqTDmfbJo+M7+xZfgBe+91N9W2teuPl/tZ6gM5d99bK+xRfggusu6Ntag2jsgx88\noPgC1LZtfOtNF1ITE32a6sB1GeATgE1Ttjf39k17TFXtAL4DHNvhTPvklrvu7+t61dfV5oHrf7H1\nBJ258o4r+7rel+77Ul/XGzQPf2ltfxbavp0d//zP/VmrD2bFTbgkFyYZTTI6NjZ20J73OU95wkF7\nLk1j+WtbT9CZ1StW93W9U5ac0tf1Bs2iU/9dfxYaGmL4iU/sz1p90GWA7waWT9le1ts37TFJhoGj\ngC27L1RVl1XVSFWNLF26tKNxH+uIQ4c5bdmRfVvv47/w7/u21rxwwZ+3nqAzv77q1/u63rVnX9vX\n9QbN0re9jcN/6AD/+7NgAT/w++8jw53d+tpnqerm/xj3gvoN4BVMhnYt8JNVdduUY94MPKuqfr53\nE+51VfWGPa07MjJSo6Ojncz8eKqKv1u3ia/fvYWFCQuGIBMLOHQ4LEz4boXFQ/DAw9uoieKJT1jM\ntkfH2boTlhwKL37mUzjl+D7foBpkB3ozbo7ffJtq6/atXD56Ofdsu4eVx62EnbBl6xaOOuwojll4\nDN+b+B6PbnuUex+9l6cf+3S2PLSFB7c9yIpjVvDAww/w+lNfzzGHH9P6xzhoavt2djz8MBCGFh/O\nrhtGO7ZuZXjxYia2bydDQ0yMjxPCxI5xMjRE7dzJwqOPbjn6tPe2OgswQJJXA38EDAEfrarfS3IJ\nMFpVa5IcBnwMOA24Hzi3qjbuac0WAZakA3TwA9wFAyxpFpo2wLPiJpwkzUUGWJIaMcCS1IgBlqRG\nDLAkNWKAJakRAyxJjRhgSWrEAEtSIwZYkhoxwJLUyKz7LIgkY8A3W88xjeOA+1oPMUv4Wu0bX6+Z\nG9TX6r6qesyHQM+6AA+qJKNVNdJ6jtnA12rf+HrN3Gx7rbwEIUmNGGBJasQA989lrQeYRXyt9o2v\n18zNqtfKa8CS1IhnwJLUiAGWpEYM8AFKsjrJ+iQbklzcep5BluSjSe5N8vXWs8wWSYaSfDnJJ1vP\nMuiS3JXka0m+kmRWfHGkAT4ASYaAS4FXASuB85KsbDvVQLsceMyb0bVHbwXuaD3ELPKyqnrubHkv\nsAE+MKcDG6pqY1VtB64Czmo808Cqqk8D97eeY7ZIsgz4MeBPW8+ibhjgA3MCsGnK9ubePqkf/gj4\nz8BE60FmiQJuTHJLkgtbDzMTBlgaQEleA9xbVbe0nmUW+eGqeh6TlwTfnORHWg+0Nwb4wNwNLJ+y\nvay3TzpQLwLOTHIXk5e2Xp7kz9uONNiq6u7en/cCH2fyEuFAM8AHZi1wUpITkxwCnAusaTyT5oCq\n+o2qWlZVK5j89+pTVXV+47EGVpLFSZbs+jvwo8DAv9vGAB+AqtoBXATcwOSd6muq6ra2Uw2uJFcC\nXwBOSbI5yQWtZ9Kc8STgs0nWAV8Crquq6xvPtFf+KrIkNeIZsCQ1YoAlqREDLEmNGGBJasQAS1Ij\nBliSGjHAGnhJ3pXk1/bjn7skyRl9mmFFkp/sx1rSLgZYc1ZVvbOq/r5Py60ADLD6ygBrICV5R5Jv\nJPkscEpv3w8mub73aVefSfKMJEcl+WaSBb1jFifZlGRhksuTvL63/wVJPp9kXZIvJVnS+7Dz9ydZ\nm+SrSX5uDyO9F3hx78O+fyXJp5M8d8q8n03ynN7Z+seSfCHJPyV505Rj3j7lud7dyQunWWW49QDS\n7pI8n8nPP3guk/+O3grcwuQ33v58Vf1TklXAh6vq5Um+ArwEuAl4DXBDVY0n2bXeIcDVwDlVtTbJ\nkcBW4ALgO1X1giSHAp9LcmNV3TnNWBcDv1ZVr+mteT/wRuCXk5wMHFZV65KcDTwbeCGwGPhykuuA\nU4GTmPyAmABrkvxI7zOSNU8ZYA2iFwMfr6pHAJKsAQ4Dfgi4dldYgUN7f14NnMNkgM8FPrzbeqcA\n366qtQBV9d3euj8KPHvXWTJwFJORnC7Au7sW+O0kbwd+hslv+9jlE1W1Fdia5CYmo/vDTH5AzJd7\nxxzRey4DPI8ZYM0WC4AHq+q50zy2BnhPkmOA5wOfmuGaAd5SVTfs6zBV9UiS/8PkN6C8ofe83394\n98N7z/Vfquoj+/pcmru8BqxB9Gngx5Ms6n3E4GuBR4A7k/wEQCY9B6CqHmLyo0E/CHyyqnbutt56\n4PgkL+j9s0uSDDP5KXa/kGRhb//JvY8ynM73gCW77ftT4I+BtVX1wJT9ZyU5LMmxwEt7s90A/EyS\nI3rPdUKSJ+7by6K5xjNgDZyqujXJ1cA64F4mAwbwH4E/SfJbwEImP6h8Xe+xq5m8LPDSadbbnuQc\n4ENJFjF5/fcMJgO6Arg1k9c1xoAff5yxvgrs7H3c4eVV9YGquiXJd4H/Oc2xNwHHAb9bVfcA9yR5\nJvCF3iWUh4Dzez+f5ik/jlLaT0l+APhH4BlVNdHb9y7goar6rw1H0yzhJQhpPyT5T8AXgXfsiq+0\nrzwDlqZI8izgY7vt3lZVq1rMo7nNAEtSI16CkKRGDLAkNWKAJakRAyxJjfx/bz5Teq5hbwgAAAAA\nSUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lalooe-K14tS",
        "colab_type": "text"
      },
      "source": [
        "device_type取值为5时，click取值为0；但device_type取其他值时，click取1和0的概率基本相当。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y5AeCofR2Gxe",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "4ea7754b-7f54-482c-d623-46dfddb5e680"
      },
      "source": [
        "sns.catplot(x=\"device_conn_type\", y=\"click\", data=train_data)"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f10fb70d390>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YOVQajp52ND5",
        "colab_type": "text"
      },
      "source": [
        "device_conn_type对click的影响，有点类似于device_type, 当device_conn_type取值为5时，click大概率取0，而device_conn_type取其他值时，click取1和0的概率基本相当。"
      ]
    }
  ]
}